The 2007 jfwiii All-Stars

Or, in other words, my fantasy team. I drafted my team last night, and as usual, there were plenty of surprises during the draft. I’ll get to those in a minute, but first, I have a disclaimer/explanation:

I know no one really cares about anyone else’s fantasy baseball team, unless it’s another team in your own league. Fantasy baseball is arguably the lowest-maintenance fantasy sport, especially when you play with rotisserie (category accumulation) style scoring. That’s what I do, and I play in an NL-only league, which makes my team even less interesting to some baseball fans. At any rate, this post is mainly here to serve as an introduction to the “meat” of what I want to write about, which is my fantasy strategy, rather than just my fantasy team. I feel like I need to share the team details first, however.

*Will be dropped this week for an injury replacement…he was my last pick anyway.

Overall, I’m mildly pleased by my team. I thought the rest of the league did a fantastic job at the draft, with at least 4-5 other owners consistently taking picks off the top of my board. I’m pretty solid in every category, perhaps with an emphasis in batting average and ERA/WHIP. Obviously I’ve pretty much punted saves, but I do have two closers-in-waiting (Wheeler and Linebrink) who should help me out in the rate categories even if they never finish a game.

Where did I go wrong?

Well, the #4 pick may have been the first place, because I didn’t take the guy who was theoretically at the top of my draft board. Every year, it seems like pitchers are undervalued, but when I follow my spreadsheets, I always end up way ahead in pitching and needing to make up ground in hitting. I decided to adjust for this in my head and take an unconventional-for-me balanced hitting/pitching approach.

For a few years now, I have been using the method that noted sabermetrician Tangotiger seems to think is the most reasonable way to value players in fantasy. Basically, the idea is to take the players you expect to be drafted, find the standard deviations of each of the stat categories, and use that to figure out how many SDs above average each player is in each category. The mathematical way of saying that would be to find each player’s z-score for each category, and add them all up into one rating. You also have to find a player’s real contribution to the team in batting average, ERA, and WHIP, rather than just using the rate stats themselves. Tango explains all that and more in the post linked above, and you end up using what he calls xH (and I guess x. Then you adjust for positional strength (I use replacement level at each position) and you’re done. It’s actually simpler than it sounds, although I make a few additional adjustments during the draft to reflect my own team’s changing composition.

As it turns out, I had a bug in my spreadsheets that may have caused me not to draft ideally from the middle rounds on. I pretty much had to wing it at the end of the draft because of this bug, but I don’t think it affected my team substantially. It caused me to weight several of the categories and one of the positions improperly, but since I was mainly looking for players at specific positions at that point, it probably didn’t affect me too much.

Next, I’ll look at the standings I would predict for my league using my own player projections. It would be a shame if I didn’t come out on top using my own system, but we’ll see how I did.